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Senior Staff Data Engineer

Grainger is hiring for Senior Staff Data EngineerCompany Overview:As a leading industrial distributor with operations primarily in North America, Japan, and the United Kingdom, we keep the world working by serving more than 4.5 million customers worldwide. Our products are delivered through innovative technology and deep customer relationships. With 2023 sales of $16.5 billion, we are dedicated to providing value for customers, fostering an engaging culture for team members, and driving strong financial results. As a 2024 Glassdoor Best Place to Work and a Great Place to Work-Certified company, we are looking for passionate people to join our team and continue leading the industry over our next 100 years.Position Details:• Department: Customer Information Management (CIM)• Reports to: Manager, CIM, Product EngineeringRole Overview:We are looking for a Senior Staff Data Engineer on our CIM team. The team's primary mission is to build analytical data products by creating, gathering, maintaining, and operationalizing real-world information about our customers to drive growth actions across sales and marketing. You will help design and develop data pipelines and data products, working with SMEs, architects, analysts, data scientists, stakeholders, and others to integrate, process, and store data from various internal and external enterprise data sources.Key Responsibilities:• Enable analytics and reporting by centralizing and integrating high-quality, large, complex data sets in a scalable cloud analytical platform.• Work closely with architects, stakeholders, and product teams to implement data pipelines for data ingestion, cleansing, and enrichment.• Design and implement secure, performant data models to meet scalability and performance needs.• Understand trends and emerging technologies and evaluate their performance and applicability.• Build data models with DBT and create DBT unit tests to ensure data quality.• Build and maintain data quality dashboards in Streamlit.• Partner with data, design, product, and executive teams to assist with data-related technical issues.• Develop data products/systems using large and complex data sets to meet business and technical requirements.• Define roadmap, communication, and architecture with product and business teams.• Promote effective team practices, shape team culture, and engage in active mentoring.• Pair program with developers to ensure better quality code, shared knowledge, and increased application resiliency.• Advocate for best practices and prescribe coding and testing standards and tools.• Work across the CIM Domain to establish best practices and coherent ways of working within and between teams.Required Qualifications:• 10 years of experience with modern data engineering projects, including designing, building, and deploying scalable data pipelines.• 5+ years of experience designing, building, and deploying cloud-native solutions.• At least 3 years of experience with AWS, Snowflake, DBT, Airflow/Astronomer, Python, Docker/Kubernetes, CI/CD, Git, and familiarity with Databricks.• Experience with data lake design, data pipelines, and data product publication strategy, with familiarity with data mesh architecture.• Experience designing and implementing efficient, reusable, and scalable data processing systems and pipelines in Databricks and Snowflake.• Experience educating and mentoring junior data engineers on best practices.• Proven experience collaborating across teams to develop and implement data engineering best practices.• Exposure to analytics and machine learning.• Familiarity with BI tools such as Tableau and PowerBI.Rewards and Benefits:• Medical, dental, vision, and life insurance plans.• Generous paid time off (PTO) and 6 company holidays per year.• Automatic 6% 401(k) company contribution each pay period.• Employee discounts, parental leave, 3:1 match on donations, and tuition reimbursement.• A comprehensive set of emotional, financial, physical, and social wellbeing programs.Equal Opportunity Statement:We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. We are proud to be an equal opportunity workplace and are committed to fostering an inclusive, accessible environment. If you need a reasonable accommodation during the application and selection process, please advise us so we can provide appropriate assistance.

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What You Should Know About Senior Staff Data Engineer, Grainger

Grainger is on the lookout for a talented Senior Staff Data Engineer to join our Customer Information Management (CIM) team in Warrenville, IL! As a key player in our mission, you’ll be instrumental in building analytical data products by gathering, maintaining, and operationalizing real-world information about our customers. This is a fantastic opportunity to design and develop robust data pipelines, collaborating with subject matter experts, architects, analysts, and data scientists to integrate data from a variety of sources. You’ll enable analytics and reporting by centralizing large, complex data sets on a scalable cloud platform while implementing data pipelines for ingestion, cleansing, and enrichment. If you're passionate about data engineering and want to work in an environment that values innovation and teamwork, Grainger could be your perfect fit. In this role, you’ll not only create data models with DBT but also help shape the data culture by promoting best practices and mentoring junior engineers. We believe that great things happen when diverse teams work together, and we would love for you to be part of our journey as we continue to lead in the industry over the next century!

Frequently Asked Questions (FAQs) for Senior Staff Data Engineer Role at Grainger

What are the main responsibilities of a Senior Staff Data Engineer at Grainger?

As a Senior Staff Data Engineer at Grainger, your primary responsibilities include designing and developing data pipelines, integrating high-quality data sets, and collaborating with various teams to create analytical data products. You will also build and maintain data quality dashboards and advocate for best practices in data engineering, ensuring the team adheres to quality coding and testing standards.